{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline --no-import-all"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "exotxt ViscoplasticNeedlemanFullyPrescribedTension_NoFlaw.h ViscoplasticNeedlemanFullyPrescribedTension_NoFlaw.txt\n",
      "sed 's/-308/E-308/g' ViscoplasticNeedlemanFullyPrescribedTension_NoFlaw.txt > temp;"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "                           *** exotxt Version 1.23 ***\n",
        "                               Revised 2013/08/07                      \n",
        "\n",
        "                    EXODUSII DATABASE TO TEXT FILE TRANSLATOR\n",
        "\n",
        "                          Run on 2014-01-03 at 15:29:08\n",
        "\n",
        "               ==== Email gdsjaar@sandia.gov for support ====\n",
        "\n",
        "\n",
        " DATABASE INITIAL VARIABLES\n",
        "\n",
        " Peridigm\n",
        "\n",
        " Number of coordinates per node         =         3\n",
        " Number of nodes                        =         1\n",
        " Number of elements                     =         1\n",
        " Number of element blocks               =         1\n",
        "\n",
        " Number of node sets                    =         0\n",
        " Number of side sets                    =         0\n",
        "\n",
        " Number of global variables             =         2\n",
        " Number of variables at each node       =         0\n",
        " Number of variables at each element    =         0\n",
        "\n",
        "\n",
        "      201 time steps on the input database\n",
        "       1 time steps processed\n",
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        "     201 time steps processed\n",
        "\n",
        "    201 time steps have been written to the text file\n",
        "\n",
        " exotxt used 0.01 seconds of CPU time\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "run exoplot.py temp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "var_names"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "array(['MAX_VON_MISES_STRESS', 'MIN_VON_MISES_STRESS'], \n",
        "      dtype='|S20')"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "eng_strain_Y = time_steps*0.001/1.0e-8"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(eng_strain_Y,data_vars[-2],eng_strain_Y,data_vars[-1]);\n",
      "plt.ylabel(\"Max/Min von Mises Stress\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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MJsOKFSvsnrykpATTpk2D1WqF1WpFenq6zR1By6t1kFu40oeISAo2w//Wg9ne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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105775110>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%%bash\n",
      "rm ViscoPlasticNeedlemanFullyPrescribedTension_NoFlaw.txt temp"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    }
   ],
   "metadata": {}
  }
 ]
}